Three trends defining AI and ML strategies

Following the publication of CX Network’s Artificial Intelligence in Customer Experience 2022 report, CX Network rounds up three key findings drawn from an extensive survey of CX industry professionals. 

Drawing comparisons from the 2021 CX Network survey we assess trends in the application of Artificial Intelligence (AI) and machine learning (ML) solutions, detailing how these technologies and their application have evolved over the last year. 

Chatbots are the biggest application of AI and ML 

The survey found that the most common application of AI and ML technologies among respondents was for chatbots or virtual assistants, with 47 percent of respondents stating that they were the primary purpose of AI and ML applications. Chatbots and virtual assistants were closely followed by empowering self-service (40 percent) and improving agent performance with recommendations (35 percent). 

It is unsurprising to see widespread application of chatbots and virtual assistants given how critical they proved to be throughout the Covid-19 pandemic. When stores and offices were forced to close due to government enforced social distancing and remote working mandates, chatbots proved a vital channel of communication for customers when agent availability was impacted by the pandemic. 

With the application of AI and ML in the form of chatbots allowing businesses to continue to deliver quality customer experiences regardless of agent availability it makes sense that we are seeing increased investment in this area. 

Data challenges remain unchanged 

The primary challenges surrounding the application and management of data remain unchanged from those uncovered in the 2021 survey. Restricted data access or siloed data alongside incomplete customer profiles affect a total of 54 percent of surveyed respondents in 2022. 

The intelligent aspects of AI and ML solutions work only when the systems are supplied with extensive and accurate data. Decisions made by an AI are formed entirely based on the data they are fed. These realizations shed light on the reasons that CX survey respondents continue to flag data issues as a significant challenge to the successful implementation of AI and ML solutions. 

Further, data challenges cited by survey respondents include no or limited access to customer data (14 percent), data siloed by channel or business function (15 percent) and incomplete customer profiles (25 percent). 

AI and ML implementation is on the rise 

The number of respondents that stated their organization has no immediate plans to implement AI and ML solutions has drastically decreased since the 2021 issue of the AI in CX survey, dropping by more than half from 50 percent to 23 percent. 

This decrease suggests a rising level of confidence in AI and ML solutions as more businesses take the leap with investment into what can be very expensive technologies. This also suggests that CX practitioners are becoming more adept at demonstrating the ROI of AI and ML solutions, however survey responses indicate that there is still some way to go here. 

Despite the increasing application of AI and ML, 44 percent of respondents flagged demonstrating ROI as a major challenge, making it the third most prominent challenge on the minds of respondents. As practitioners continue to improve their ability to demonstrate the ROI of AI and ML initiatives, we will likely see their adoption increase even further. 

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